Functional magnetic resonance imaging of intrinsic brain networks for translational drug discovery

Deep learning applied to the segmentation of rodent brain MRI data outperforms noisy ground truth on full-fledged brain atlases

Translational magnetic resonance imaging of the rodent brain provides invaluable information for preclinical drug development. However, the automated segmentation of such images for quantitative analyses is limited compared to human brain imaging mainly due to the inferior anatomical contrast and the resulting less advanced registration and atlasing tools. Here, we investigated the potential of deep learning models for the segmentation of magnetic resonance images of rat brains into an entire set of multiple regions of interest (rather than individual loci), focusing on the development of a robust method that accommodates changes in the input based on differences in animal strain (genotype) and size. Manually generated labels are expensive, so we tested the ability of neural networks to learn brain structures from noisy but inexpensive registration-based labels, allowing very large datasets to be leveraged for training. We compared three distinct model architectures (U-Net, Attention-U-Net and DeepLab) by training them on a dataset of >10,000 magnetic resonance images of rat brains and found that each model was able to segment the entire brain into predefined sets of 29 and 58 regions, respectively, with the Attention U-Net achieving the best performance. The models canceled out unstructured label noise in the imperfect training data to provide smoother and more symmetric segmentations than registration-based labeling, and were more robust when presented with input variations, thus outperforming the noisy ground truth. Our pipeline also includes uncertainty estimation and an explainability mechanism, hence providing features essential for anomaly detection and quality assurance. In summary, our study shows that deep learning models do achieve accurate brain segmentation in high-throughput quantitative preclinical imaging without the need for expensive expert-generated labels.

Functional connectivity density aberrance in type 2 diabetes mellitus with and without mild cognitive impairment

Purpose

The objective of this study was to investigate alterations in functional connectivity density (FCD) mapping and their impact on functional connectivity (FC) among individuals diagnosed with Type 2 diabetes mellitus (T2DM) across different cognitive states. Moreover, the study sought to explore the potential association between aberrant FCD/FC patterns and clinical or cognitive variables.

Methods

A total of 211 participants were recruited for this study, consisting of 75 healthy controls (HCs), 89 T2DM patients with normal cognitive function (DMCN), and 47 T2DM patients with mild cognitive impairment (DMCI). The study employed FCD analysis to pinpoint brain regions exhibiting significant FCD alterations. Subsequently, these regions showing abnormal FCD served as seeds for FC analysis. Exploratory partial correlations were conducted to explore the relationship between clinical biochemical indicators, neuropsychological test scores, and altered FCD or FC.

Results

The FCD analysis revealed an increased trend in global FCD (gFCD), local FCD (lFCD), and long-range FCD (lrFCD) within the bilateral supramarginal gyrus (SMG) among individuals with DMCN. Additionally, significant lFCD alterations were observed in the right inferior frontal gyrus and left precuneus when comparing DMCN to HCs and DMCI.

Conclusion

When comparing individuals with T2DM and healthy controls (HCs), it was revealed that DMCN exhibited significant improvements in FCD. This suggests that the brain may employ specific compensatory mechanisms to maintain normal cognitive function at this stage. Our findings provide a novel perspective on the neural mechanisms involved in cognitive decline associated with T2DM.

Experimental Medicine Approaches in Early-Phase CNS Drug Development

Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development.

Altered Spontaneous Brain Activity in Patients With Diabetic Osteoporosis Using Regional Homogeneity: A Resting-State Functional Magnetic Resonance Imaging Study

Background

The pathophysiological mechanism of cognitive impairment by osteoporosis in type 2 diabetes mellitus (T2DM) remains unclear. This study aims to further investigate the regional spontaneous brain activity changes of patients with diabetic osteoporosis (DOP), and the correlation between abnormal brain regions and bone metabolites.

Methods

A total of 29 subjects with T2DM were recruited, including fourteen patients with DOP and thirteen patients without osteoporosis (Control group). Based on the resting-state functional magnetic resonance imaging (rs-fMRI) datasets acquired from all the subjects, a two-sample t-test was performed on individual normalized regional homogeneity (ReHo) maps. Spearman correlation analysis was performed between the abnormal ReHo regions with the clinical parameters and Montreal Cognitive Assessment (MOCA) scores.

Results

In the DOP group, we demonstrated the significantly increased ReHo values in the left middle temporal gyrus (MTG), right superior occipital gyrus (SOG), aright superior parietal lobule (SPL), right angular gyrus (AG), and left precuneus (PE). Additionally, we also found a significant positive correlation between increased ReHo values in the left MTG and the average bone mineral density (BMD AVG), and average T scores (T AVG). The ReHo values of the right SOG and right SPL showed a negative correlation with MOCA scores, as well as a negative correlation between increased ReHo values in the right SPL and osteocalcin (OC) level.

Conclusion

Patients with DOP showed increased spontaneous activity in multiple brain regions. The results indicated that osteoporosis exacerbated cognitive impairment and brain damage. Also, the OC might be considered as a bone marker to track the progression of cognitive impairment.

Role of Brain Imaging in Drug Development for Psychiatry

Background:

Over the last decades, many brain imaging studies have contributed to new insights in the pathogenesis of psychiatric disease. However, in spite of these developments, progress in the development of novel therapeutic drugs for prevalent psychiatric health conditions has been limited.

Objective:

In this review, we discuss translational, diagnostic and methodological issues that have hampered drug development in CNS disorders with a particular focus on psychiatry. The role of preclinical models is critically reviewed and opportunities for brain imaging in early stages of drug development using PET and fMRI are discussed. The role of PET and fMRI in drug development is reviewed emphasizing the need to engage in collaborations between industry, academia and phase I units.

Conclusion:

Brain imaging technology has revolutionized the study of psychiatric illnesses, and during the last decade, neuroimaging has provided valuable insights at different levels of analysis and brain organization, such as effective connectivity (anatomical), functional connectivity patterns and neurochemical information that may support both preclinical and clinical drug development. Since there is no unifying pathophysiological theory of individual psychiatric syndromes and since many symptoms cut across diagnostic boundaries, a new theoretical framework has been proposed that may help in defining new targets for treatment and thus enhance drug development in CNS diseases. In addition, it is argued that new proposals for data-mining and mathematical modelling as well as freely available databanks for neural network and neurochemical models of rodents combined with revised psychiatric classification will lead to new validated targets for drug development.

A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes

Neuroimaging studies have identified brain structural and functional alterations of type 2 diabetes mellitus (T2DM) patients; however, there is no systematic information on the relations between abnormalities in these two domains. We conducted a multimodal meta-analysis of voxel-based morphometry and regional resting-state functional MRI studies in T2DM, including fifteen structural datasets (693 patients and 684 controls) and sixteen functional datasets (378 patients and 358 controls). We found, in patients with T2DM compared to controls, conjoint decreased regional gray matter volume (GMV) and altered intrinsic activity mainly in the default mode network including bilateral superior temporal gyrus/Rolandic operculum, left middle and inferior temporal gyrus, and left supramarginal gyrus; decreased GMV alone in the limbic system; and functional abnormalities alone in the cerebellum, insula, and visual cortex. This meta-analysis identified complicated patterns of conjoint and dissociated brain alterations in T2DM patients, which may help provide new insight into the neuropathology of T2DM.

Utility of Preoperative Blood-Oxygen-Level-Dependent Functional MR Imaging in Patients with a Central Nervous System Neoplasm

Functional neuroimaging provides means to understand the relationship between brain structure and associated functions. Functional MR (fMR) imaging can offer a unique insight into preoperative planning for central nervous system (CNS) neoplasms by identifying areas of the brain effected or spared by the neoplasm. BOLD (blood-oxygen-level-dependent) fMR imaging can be reliably used to map eloquent cortex presurgically and is sufficiently accurate for neurosurgical planning. In patients with brain tumors undergoing neurosurgical intervention, fMR imaging can decrease postoperative morbidity. This article discusses the applications, significance, and interpretation of BOLD fMR imaging, and its applications in presurgical planning for CNS neoplasms.

Aberrant Functional Connectivity of the Posterior Cingulate Cortex in Type 2 Diabetes Without Cognitive Impairment and Microvascular Complications

OBJECTIVE

We aimed to investigate the alterations of brain functional connectivity (FC) in type 2 diabetes mellitus (T2DM) patients without clinical evidence of cognitive impairment and microvascular complications (woCIMC-T2DM) using resting-state functional MRI (rs-fMRI) and to determine whether its value was correlated with clinical indicators.

METHODS

A total of 27 T2DM and 26 healthy controls (HCs) were prospectively examined. Cognitive impairment was excluded using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) scales, and microvascular complications were excluded by fundus photography, microalbuminuria, and other indicators. The correlation maps, derived from rs-fMRI with posterior cingulate cortex (PCC) as the seed, were compared between T2DM patients and HCs. Pearson's correlation analysis was performed to determine the relationship between the FC of PCC and the clinical indicators.

RESULTS

Compared with HC, woCIMC-T2DM patients showed significantly decreased FCs with PCC (PCC-FCs) in the anterior cingulate cortex (ACC), right superior frontal gyrus, right medial frontal gyrus, and right angular gyrus. Meanwhile, increased PCC-FCs was observed in the right superior temporal gyrus and calcarine fissure (CAL). The FC of PCC-ACC was negatively correlated with glycosylated hemoglobin (HbA1c) and diabetes duration, and the FC of PCC-CAL was significantly positively correlated with HbA1c and diabetes duration.

CONCLUSION

The FC, especially of the PCC with cognitive and visual brain regions, was altered before clinically measurable cognitive impairment and microvascular complications occurred in T2DM patients. In addition, the FC of the PCC with cognitive and visual brain regions was correlated with HbA1c and diabetes duration. This indicates that clinicians should pay attention not only to blood glucose control but also to brain function changes before the occurrence of adverse complications, which is of great significance for the prevention of cognitive dysfunction and visual impairment.

Sensitivity of Neuroimaging Indicators in Monitoring the Effects of Interferon Gamma Treatment in Friedreich's Ataxia

The identification of efficient markers of disease progression and response to possibly effective treatments is a key priority for slowly progressive, rare and neurodegenerative diseases, such as Friedreich’s ataxia. Various imaging modalities have documented specific abnormalities in Friedreich’s ataxia that could be tracked to provide useful indicators of efficacy in clinical trials. Advanced MRI imaging (diffusion tensor imaging, DTI; functional MRI, fMRI; and resting-state fMRI, rs-fMRI) and retinal imaging (optical coherence tomography, OCT) were tested longitudinally in a small group of Friedreich’s ataxia patients participating in an open-label clinical trial testing the safety and the efficacy of 6-month treatment with interferon gamma. While the DTI indices documented the slow progression of fractional anisotropy loss, fMRI and rs-fMRI were significantly modified during and after treatment. The fMRI changes significantly correlated with the Scale for the Assessment and Rating of Ataxia, which is used to monitor clinical response. OCT documented the known thickness reduction of the retinal nerve fiber layer thickness, but there was no change over time. This pilot study provides indications for the potential utility of fMRI and rs-fMRI as ancillary measures in clinical trials for Friedreich’s ataxia.

Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders

Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured with functional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here a putative mechanism reported in neurodevelopmental disorders, that is, excitation-to-inhibition ratio (E:I), was chemogenetically increased within cortical microcircuits of the mouse brain and measured via fMRI. Increased E:I caused a significant "reduction" of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin (PV) interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knockout mice, a model for autism with well-documented loss of parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.

Utility of Preoperative Blood-Oxygen-Level-Dependent Functional MR Imaging in Patients with a Central Nervous System Neoplasm

Functional neuroimaging provides means to understand the relationship between brain structure and associated functions. Functional MR (fMR) imaging can offer a unique insight into preoperative planning for central nervous system (CNS) neoplasms by identifying areas of the brain effected or spared by the neoplasm. BOLD (blood-oxygen-level-dependent) fMR imaging can be reliably used to map eloquent cortex presurgically and is sufficiently accurate for neurosurgical planning. In patients with brain tumors undergoing neurosurgical intervention, fMR imaging can decrease postoperative morbidity. This article discusses the applications, significance, and interpretation of BOLD fMR imaging, and its applications in presurgical planning for CNS neoplasms.

Neural and neuronal discoordination in schizophrenia: From ensembles through networks to symptoms

Despite the substantial knowledge accumulated by past research, the exact mechanisms of the pathogenesis of schizophrenia and causal treatments still remain unclear. Deficits of cognition and information processing in schizophrenia are today often viewed as the primary and core symptoms of this devastating disorder. These deficits likely result from disruptions in the coordination of neuronal and neural activity. The aim of this review is to bring together convergent evidence of discoordinated brain circuits in schizophrenia at multiple levels of resolution, ranging from principal cells and interneurons, neuronal ensembles and local circuits, to large-scale brain networks. We show how these aberrations could underlie deficits in cognitive control and other higher order cognitive-behavioural functions. Converging evidence from both animal models and patients with schizophrenia is presented in an effort to gain insight into common features of deficits in the brain information processing in this disorder, marked by disruption of several neurotransmitter and signalling systems and severe behavioural outcomes.

Hypersynchronicity in the default mode-like network in a neurodevelopmental animal model with relevance for schizophrenia

BACKGROUND

Immune activation during pregnancy is an important risk factor for schizophrenia. Brain dysconnectivity and NMDA receptor (NMDAR) hypofunction have been postulated to be central to schizophrenia pathophysiology. The aim of this study was to investigate resting-state functional connectivity (resting-state functional MRI-rsfMRI), microstructure (diffusion tension imaging-DTI) and response to NMDAR antagonist (pharmacological fMRI-phMRI) using multimodal MRI in offspring of pregnant dams exposed to immune challenge (maternal immune activation-MIA model), and determine whether these neuroimaging readouts correlate with schizophrenia-related behaviour.

METHODS

Pregnant rats were injected with Poly I:C or saline on gestational day 15. The maternal weight response was assessed. Since previous research has shown behavioural deficits can differ between MIA offspring dependent on the maternal response to immune stimulus, offspring were divided into three groups: controls (saline, n = 11), offspring of dams that gained weight (Poly I:C WG, n = 12) and offspring of dams that lost weight post-MIA (Poly I:C WL, n = 16). Male adult offspring were subjected to rsfMRI, DTI, phMRI with NMDAR antagonist, behavioural testing and histological assessment.

RESULTS

Poly I:C WL offspring exhibited increased functional connectivity in default mode-like network (DMN). Poly I:C WG offspring showed the most pronounced attenuation in NMDAR antagonist response versus controls. DTI revealed no differences in Poly I:C offspring versus controls. Poly I:C offspring exhibited anxiety.

CONCLUSIONS

MIA offspring displayed a differential pathophysiology depending on the maternal response to immune challenge. While Poly I:C WL offspring displayed hypersynchronicity in the DMN, altered NMDAR antagonist response was most pronounced in Poly I:C WG offspring.

The affinity of antipsychotic drugs to dopamine and serotonin 5-HT2 receptors determines their effects on prefrontal-striatal functional connectivity

One of the major challenges of cross-species translation in psychiatry is the identification of quantifiable brain phenotypes linked to drug efficacy and/or side effects. A measure that has received increasing interest is the effect of antipsychotic drugs on resting-state functional connectivity (FC) in magnetic resonance imaging. However, quantitative comparisons of antipsychotic drug-induced alterations of FC patterns are missing. Consideration of receptor binding affinities provides a means for the effects of antipsychotic drugs on extended brain networks to be related directly to their molecular mechanism of action. Therefore, we examined the relationship between the affinities of three second-generation antipsychotics (amisulpride, risperidone and olanzapine) to dopamine and serotonin receptors and FC patterns related to the prefrontal cortex (PFC) and striatum in Sprague-Dawley rats. FC of the relevant regions was quantified by correlation coefficients and local network properties. Each drug group (32 animals per group) was subdivided into three dose groups and a vehicle control group. A linear relationship was discovered for the mid-dose of antipsychotic compounds, with stronger affinity to serotonin 5-HT_2A, 5-HT_2C and 5-HT_1A receptors and decreased affinity to D₃ receptors associated with increased prefrontal-striatal FC (p = 0.0004, r² = 0.46; p = 0.004, r² = 0.33; p = 0.002, r² = 0.37; p = 0.02, r² = 0.22, respectively). Interestingly, no correlation was observed for the low and high dose groups, and for D₂ receptors. Our results indicate that drug-induced FC patterns may be linked to antipsychotic mechanism of action on the molecular level and suggest the technique's value for drug development, especially if our results are extended to a larger number of antipsychotics.

Subgraphs of functional brain networks identify dynamical constraints of cognitive control

Brain anatomy and physiology support the human ability to navigate a complex space of perceptions and actions. To maneuver across an ever-changing landscape of mental states, the brain invokes cognitive control-a set of dynamic processes that engage and disengage different groups of brain regions to modulate attention, switch between tasks, and inhibit prepotent responses. Current theory posits that correlated and anticorrelated brain activity may signify cooperative and competitive interactions between brain areas that subserve adaptive behavior. In this study, we use a quantitative approach to identify distinct topological motifs of functional interactions and examine how their expression relates to cognitive control processes and behavior. In particular, we acquire fMRI BOLD signal in twenty-eight healthy subjects as they perform two cognitive control tasks-a Stroop interference task and a local-global perception switching task using Navon figures-each with low and high cognitive control demand conditions. Based on these data, we construct dynamic functional brain networks and use a parts-based, network decomposition technique called non-negative matrix factorization to identify putative cognitive control subgraphs whose temporal expression captures distributed network structures involved in different phases of cooperative and competitive control processes. Our results demonstrate that temporal expression of the subgraphs fluctuate alongside changes in cognitive demand and are associated with individual differences in task performance. These findings offer insight into how coordinated changes in the cooperative and competitive roles of cognitive systems map trajectories between cognitively demanding brain states.

Advances in Drug Discovery and Development in Geriatric Psychiatry

PURPOSE OF REVIEW

This article reviews recent advances in drug discovery and development for geriatric psychiatry. Drug discovery for disorders of the central nervous system is a long and challenging process, with a high attrition rate from the preclinical stages through to marketing a compound. Developing drugs for geriatric neuropsychiatric conditions presents additional challenges, due to the complexity of the symptoms, comorbid diagnoses, and the variability of the population. Despite there being limited success over the past two decades, a number of new approaches have identified potential targets for preclinical development and ultimately clinical testing.

RECENT FINDINGS

Recent approaches have tried to address specific mechanisms that relate to the disease progression. These approaches include combining a number of ligands into to multi-target compounds, or targeting specific types of cells such as protein kinases or myeloid cells. In addition, the increased use of induced pluripotent stem cell cultures has enabled new compounds to be tested on disease-specific tissues, increasing the success rate of the lead compounds going through the preclinical stages. New pharmacological agents designed with advanced screening techniques and the shift towards systems pharmacology is changing the landscape of drug discovery in geriatric psychiatry. There is potential for these new agents to produce targeted effects in the framework of disorders that have long been untreatable.

From Maps to Multi-dimensional Network Mechanisms of Mental Disorders

The development of advanced neuroimaging techniques and their deployment in large cohorts has enabled an assessment of functional and structural brain network architecture at an unprecedented level of detail. Across many temporal and spatial scales, network neuroscience has emerged as a central focus of intellectual efforts, seeking meaningful descriptions of brain networks and explanatory sets of network features that underlie circuit function in health and dysfunction in disease. However, the tools of network science commonly deployed provide insight into brain function at a fundamentally descriptive level, often failing to identify (patho-)physiological mechanisms that link system-level phenomena to the multiple hierarchies of brain function. Here we describe recently developed techniques stemming from advances in complex systems and network science that have the potential to overcome this limitation, thereby contributing mechanistic insights into neuroanatomy, functional dynamics, and pathology. Finally, we build on the Research Domain Criteria framework, highlighting the notion that mental illnesses can be conceptualized as dysfunctions of neural circuitry present across conventional diagnostic boundaries, to sketch how network-based methods can be combined with pharmacological, intermediate phenotype, genetic, and magnetic stimulation studies to probe mechanisms of psychopathology.

Targeting Functional Biomarkers in Schizophrenia with Neuroimaging

Many of the most debilitating symptoms for psychiatric disorders such as schizophrenia remain poorly treated. As such, the development of novel treatments is urgently needed. Unfortunately, the costs associated with high failure rates for investigational compounds as they enter clinical trials has led to pharmaceutical companies downsizing or eliminating research programs needed to develop these drugs. One way of increasing the probability of success for investigational compounds is to incorporate alternative methods of identifying biological targets in order to more effectively screen new drugs. A promising method of accomplishing this goal for psychiatric drugs is to use functional magnetic resonance imaging (fMRI). fMRI investigates neural circuits, shedding light on the biology that generates symptoms such as hallucinations. Once identified, relevant neural circuits can be targeted with pharmacologic interventions and the response to these drugs measured with fMRI. This review describes the early use of fMRI in this context, and discusses the alpha7 nicotinic receptor agonist 3-(2,4-dimethoxybenzylidene) anabaseine (DMXB-A), as an example of the potential value of fMRI for psychiatric drug development.

EEG Source Reconstruction in Male Nonsmokers after Nicotine Administration during the Resting State

Modern psychopharmacological research in humans focuses on how specific psychoactive molecules modulate oscillatory brain activity. We present state-of-the-art EEG methods applied in a resting-state drug study. Thirty healthy male nonsmokers were randomly allocated either to a nicotine group (14 subjects, 7 mg transdermal nicotine) or a placebo group (16 subjects). EEG activity was recorded in eyes-open (EO) and eyes-closed (EC) conditions before and after drug administration. A source reconstruction (minimum norm algorithm) analysis was conducted within a frequency range of 8.5-18.4 Hz subdivided into three different frequency bands. During EO, nicotine reduced the power of oscillatory activity in the 12.5- to 18.4-Hz frequency band in the left middle frontal gyrus. In contrast, in the EC condition, nicotine reduced the power in the 8.5- to 10.4-Hz frequency band in the superior frontal gyri and in the 10.5- to 12.4-Hz and 12.5- to 18.4-Hz frequency bands in the supplementary motor areas. In summary, nicotine reduced the power of the 12.5- to 18.4-Hz band in the left middle frontal gyrus during EO, and it reduced power from 8.5 to 18.4 Hz in a brain area spanning from the superior frontal gyri to the supplementary motor areas during EC. In conclusion, the results suggest that nicotine counteracts the phenomenon of anteriorization of α activity, hence potentially increasing the level of vigilance.

Hippocampal-prefrontal connectivity as a translational phenotype for schizophrenia

Finding novel biological targets in psychiatry has been difficult, partly because current diagnostic categories are not defined by pathophysiology and difficult to model in animals. The study of species-conserved systems-level mechanisms implicated in psychiatric disease could be a promising strategy to address some of these difficulties. Altered hippocampal-prefrontal (HC-PFC) connectivity during working memory (WM) processing is a candidate for such a translational phenotype as it has been repeatedly associated with impaired cognition in schizophrenia patients and animal models for psychiatric risk factors. Specifically, persistent hippocampus-dorsolateral prefrontal cortex (HC-DLPFC) coupling during WM is an intermediate phenotype for schizophrenia that has been observed in patients, healthy relatives and carriers of two different risk polymorphisms identified in genome-wide association studies. Rodent studies report reduced coherence between HC and PFC during anesthesia, sleep and task performance in both genetic, environmental and neurodevelopmental models for schizophrenia. We discuss several challenges for translation including differences in anatomy, recording modalities and WM paradigms and suggest that a better understanding of HC-PFC coupling across species can be achieved if translational neuroimaging is used to control for task differences. The evidence for potential neurobiological substrates underlying HC-PFC dysconnectivity is evaluated and research strategies are proposed that aim to bridge the gap between findings from large-scale association studies and disease mechanisms.

Converging effects of diverse treatment modalities on frontal cortex in schizophrenia: A review of longitudinal functional magnetic resonance imaging studies

OBJECTIVES

A variety of treatment options exist for schizophrenia, but the effects of these treatments on brain function are not clearly understood. To facilitate the development of more effective treatment strategies, it is important to identify how brain function in schizophrenia patients is affected by the diverse therapeutic approaches that are currently available. The aim of the present article is to systematically review the evidence for functional brain changes associated with different treatment modalities for schizophrenia.

METHODS

We searched PubMed for longitudinal functional MRI (fMRI) studies reporting on the effects of antipsychotic medications (APM), repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), cognitive remediation therapy (CRT) and cognitive behavioral therapy for psychosis (CBTp) on brain function in schizophrenia.

RESULTS

Thirty six studies fulfilled the inclusion criteria. Functional alterations were observed in diverse brain regions. Across intervention modalities, changes in fMRI parameters were reported most commonly in frontal brain regions including prefrontal cortex, anterior cingulate and inferior frontal cortex.

CONCLUSIONS

We conclude that current treatments for schizophrenia commonly induce functional brain alterations in frontal brain regions. However, interpretability is limited by inconsistency in task and region of interest selection, and failures to replicate. Further task independent fMRI studies examining treatment effects with whole brain analysis are needed to deepen our insights.

Oxytocin and Schizophrenia Spectrum Disorders

In this chapter, we present an overview of studies of oxytocin (OXT) in schizophrenia and the schizophrenia spectrum. We first outline the current state of pharmacological treatment of the symptoms of schizophrenia and point to unmet clinical needs. These relate particularly to the debilitating negative symptoms and social cognitive deficits that are frequently observed in patients suffering from schizophrenia. We argue that new treatments are needed to alleviate these impairments. As OXT has been proposed and investigated as a putative treatment, we will then summarise evidence from studies in patients with schizophrenia that have investigated the effects of OXT at several levels, i.e. at the levels of clinical symptoms, social cognitive function as assessed with experimental and neuropsychological tasks, and brain function as assessed using functional magnetic resonance imaging (fMRI). Finally, we will introduce the concept of the schizophrenia spectrum and highlight the importance of studying OXT effects in subclinical spectrum samples, such as in people with high levels of schizotypal personality. We conclude that the evidence of beneficial effects of OXT in schizophrenia is inconsistent, calling for further research in this field.

Can Mouse Imaging Studies Bring Order to Autism Connectivity Chaos?

Functional Magnetic Resonance Imaging (fMRI) has consistently highlighted impaired or aberrant functional connectivity across brain regions of autism spectrum disorder (ASD) patients. However, the manifestation and neural substrates of these alterations are highly heterogeneous and often conflicting. Moreover, their neurobiological underpinnings and etiopathological significance remain largely unknown. A deeper understanding of the complex pathophysiological cascade leading to aberrant connectivity in ASD can greatly benefit from the use of model organisms where individual pathophysiological or phenotypic components of ASD can be recreated and investigated via approaches that are either off limits or confounded by clinical heterogeneity. Despite some obvious limitations in reliably modeling the full phenotypic spectrum of a complex developmental disorder like ASD, mouse models have played a central role in advancing our basic mechanistic and molecular understanding of this syndrome. Recent progress in mouse brain connectivity mapping via resting-state fMRI (rsfMRI) offers the opportunity to generate and test mechanistic hypotheses about the elusive origin and significance of connectional aberrations observed in autism. Here we discuss recent progress toward this goal, and illustrate initial examples of how the approach can be employed to establish causal links between ASD-related mutations, developmental processes, and brain connectional architecture. As the spectrum of genetic and pathophysiological components of ASD modeled in the mouse is rapidly expanding, the use of rsfMRI can advance our mechanistic understanding of the origin and significance of the connectional alterations associated with autism, and their heterogeneous expression across patient cohorts.

Probing Intrinsic Resting-State Networks in the Infant Rat Brain

Resting-state functional magnetic resonance imaging (rs-fMRI) measures spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signal in the absence of external stimuli. It has become a powerful tool for mapping large-scale brain networks in humans and animal models. Several rs-fMRI studies have been conducted in anesthetized and awake adult rats, reporting consistent patterns of brain activity at the systems level. However, the evolution to adult patterns of resting-state activity has not yet been evaluated and quantified in the developing rat brain. In this study, we hypothesized that large-scale intrinsic networks would be easily detectable but not fully established as specific patterns of activity in lightly anesthetized 2-week-old rats (N = 11). Independent component analysis (ICA) identified 8 networks in 2-week-old-rats. These included Default mode, Sensory (Exteroceptive), Salience (Interoceptive), Basal Ganglia-Thalamic-Hippocampal, Basal Ganglia, Autonomic, Cerebellar, as well as Thalamic-Brainstem networks. Many of these networks consisted of more than one component, possibly indicative of immature, underdeveloped networks at this early time point. Except for the Autonomic network, infant rat networks showed reduced connectivity with subcortical structures in comparison to previously published adult networks. Reported slow fluctuations in the BOLD signal that correspond to functionally relevant resting-state networks in 2-week-old rats can serve as an important tool for future studies of brain development in the settings of different pharmacological applications or disease.

Nicotine restores functional connectivity of the ventral attention network in schizophrenia

While previous work has suggested that nicotine may transiently improve attention deficits in schizophrenia, the neuronal mechanisms are poorly understood. This study is the first to examine the effects of nicotine on connectivity within the ventral attention network (VAN) during a selective attention task in schizophrenia. Using a crossover design, 17 nonsmoking patients with schizophrenia and 20 age/gender-matched nonsmoking healthy controls performed a go/no-go task with environmental noise distractors during application of a 7 mg nicotine or placebo patch. Psychophysiological interaction analysis was performed to analyze task-associated changes in connectivity between a ventral parietal cortex (VPC) seed and the inferior frontal gyrus (IFG), key components of the human VAN. Effects of nicotine on resting state VAN connectivity were also examined. A significant diagnosis × drug interaction was observed on task-associated connectivity between the VPC seed and the left IFG (F(1,35) = 8.03, p < 0.01). This effect was driven by decreased connectivity after placebo in patients and greater connectivity after nicotine. Resting state connectivity analysis showed a significant main effect of diagnosis between the seed and right IFG (F = 4.25, p = 0.023) due to increased connectivity in patients during placebo, but no drug × diagnosis interactions or main effects of drug. This study is the first to demonstrate that 1) the VAN is disconnected in schizophrenia during selective attention, and 2) nicotine may normalize this pathological state.

Species-conserved reconfigurations of brain network topology induced by ketamine

Species-conserved (intermediate) phenotypes that can be quantified and compared across species offer important advantages for translational research and drug discovery. Here, we investigate the utility of network science methods to assess the pharmacological alterations of the large-scale architecture of brain networks in rats and humans. In a double-blind, placebo-controlled, cross-over study in humans and a placebo-controlled two-group study in rats, we demonstrate that the application of ketamine leads to a topological reconfiguration of large-scale brain networks towards less-integrated and more-segregated information processing in both the species. As these alterations are opposed to those commonly observed in patients suffering from depression, they might indicate systems-level correlates of the antidepressant effect of ketamine.

Functional Connectivity Hubs and Networks in the Awake Marmoset Brain

In combination with advances in analytical methods, resting-state fMRI is allowing unprecedented access to a better understanding of the network organization of the brain. Increasing evidence suggests that this architecture may incorporate highly functionally connected nodes, or “hubs”, and we have recently proposed local functional connectivity density (lFCD) mapping to identify highly-connected nodes in the human brain. Here, we imaged awake nonhuman primates to test whether, like the human brain, the marmoset brain contains FC hubs. Ten adult common marmosets (Callithrix jacchus) were acclimated to mild, comfortable restraint using individualized helmets. Following restraint training, resting BOLD data were acquired during eight consecutive 10 min scans for each subject. lFCD revealed prominent cortical and subcortical hubs of connectivity across the marmoset brain; specifically, in primary and secondary visual cortices (V1/V2), higher-order visual association areas (A19M/V6[DM]), posterior parietal and posterior cingulate areas (PGM and A23b/A31), thalamus, dorsal and ventral striatal areas (caudate, putamen, lateral septal nucleus, and anterior cingulate cortex (A24a). lFCD hubs were highly connected to widespread areas of the brain, and further revealed significant network-network interactions. These data provide a baseline platform for future investigations in a nonhuman primate model of the brain’s network topology.

Altering the course of schizophrenia: progress and perspectives

Despite a lack of recent progress in the treatment of schizophrenia, our understanding of its genetic and environmental causes has considerably improved, and their relationship to aberrant patterns of neurodevelopment has become clearer. This raises the possibility that 'disease-modifying' strategies could alter the course to - and of - this debilitating disorder, rather than simply alleviating symptoms. A promising window for course-altering intervention is around the time of the first episode of psychosis, especially in young people at risk of transition to schizophrenia. Indeed, studies performed in both individuals at risk of developing schizophrenia and rodent models for schizophrenia suggest that pre-diagnostic pharmacotherapy and psychosocial or cognitive-behavioural interventions can delay or moderate the emergence of psychosis. Of particular interest are 'hybrid' strategies that both relieve presenting symptoms and reduce the risk of transition to schizophrenia or another psychiatric disorder. This Review aims to provide a broad-based consideration of the challenges and opportunities inherent in efforts to alter the course of schizophrenia.

Brain oscillations in bipolar disorder and lithium-induced changes

Electroencephalography (EEG) studies in patients with bipolar disorder have revealed lower amplitudes in brain oscillations. The aim of this review is to describe lithium-induced EEG changes in bipolar disorder and to discuss potential underlying factors. A literature survey about lithium-induced EEG changes in bipolar disorder was performed. Lithium consistently enhances magnitudes of brain oscillations in slow frequencies (delta and theta) in both resting-state EEG studies as well as event-related oscillations studies. Enhancement of magnitudes of beta oscillations is specific to event-related oscillations. Correlation between serum lithium levels and brain oscillations has been reported. Lithium-induced changes in brain oscillations might correspond to lithium-induced alterations in neurotransmitters, signaling cascades, plasticity, brain structure, or biophysical properties of lithium. Therefore, lithium-induced changes in brain oscillations could be promising biomarkers to assess the molecular mechanisms leading to variability in efficacy. Since the variability of lithium response in bipolar disorder is due to the genetic differences in the mechanisms involving lithium, it would be highly promising to assess the lithium-induced EEG changes as biomarkers in genetic studies.

Relating Translational Neuroimaging and Amperometric Endpoints: Utility for Neuropsychiatric Drug Discovery

Measures of neuronal activation are a natural and parsimonious translational biomarker to consider in the context of neuropsychiatric drug discovery studies. In this regard, functional neuroimaging using the BOLD fMRI technique is becoming more frequently employed to not only probe aberrant brain regions and circuits in disease, but also to assess the effects of novel pharmacological agents on these processes. In the ideal situation, these types of studies would first be conducted pre-clinically in rodents to confirm a measurable functional response on relevant brain circuits before seeking to replicate the findings in an analogous fMRI paradigm in humans. However, the need for animal immobilization during the scanning procedure precludes all but the simplest behavioural task-based paradigms in rodent BOLD fMRI. This chapter considers how in vivo oxygen amperometry may represent a viable and valid proxy for BOLD fMRI in freely moving rodents engaged in behavioural tasks. The amperometric technique and several examples of emerging evidence are described to show how the technique can deliver results that translate to pharmacological, event-related and functional connectivity variants of fMRI. In vivo oxygen amperometry holds great promise as a technique that may help to bridge the gap between basic drug discovery research in rodents and applied efficacy testing in humans.

On-Going Frontal Alpha Rhythms Are Dominant in Passive State and Desynchronize in Active State in Adult Gray Mouse Lemurs

The gray mouse lemur (Microcebus murinus) is considered a useful primate model for translational research. In the framework of IMI PharmaCog project (Grant Agreement n°115009, www.pharmacog.org), we tested the hypothesis that spectral electroencephalographic (EEG) markers of motor and locomotor activity in gray mouse lemurs reflect typical movement-related desynchronization of alpha rhythms (about 8–12 Hz) in humans. To this aim, EEG (bipolar electrodes in frontal cortex) and electromyographic (EMG; bipolar electrodes sutured in neck muscles) data were recorded in 13 male adult (about 3 years) lemurs. Artifact-free EEG segments during active state (gross movements, exploratory movements or locomotor activity) and awake passive state (no sleep) were selected on the basis of instrumental measures of animal behavior, and were used as an input for EEG power density analysis. Results showed a clear peak of EEG power density at alpha range (7–9 Hz) during passive state. During active state, there was a reduction in alpha power density (8–12 Hz) and an increase of power density at slow frequencies (1–4 Hz). Relative EMG activity was related to EEG power density at 2–4 Hz (positive correlation) and at 8–12 Hz (negative correlation). These results suggest for the first time that the primate gray mouse lemurs and humans may share basic neurophysiologic mechanisms of synchronization of frontal alpha rhythms in awake passive state and their desynchronization during motor and locomotor activity. These EEG markers may be an ideal experimental model for translational basic (motor science) and applied (pharmacological and non-pharmacological interventions) research in Neurophysiology.

Decoding Advances in Psychiatric Genetics: A Focus on Neural Circuits in Rodent Models

Appropriately powered genome-wide association studies combined with deep-sequencing technologies offer the prospect of real progress in revealing the complex biological underpinnings of schizophrenia and other psychiatric disorders. Meanwhile, recent developments in genome engineering, including CRISPR, constitute better tools to move forward with investigating these genetic leads. This review aims to assess how these advances can inform the development of animal models for psychiatric disease, with a focus on schizophrenia and in vivo electrophysiological circuit-level measures with high potential as disease biomarkers.

Triptans disrupt brain networks and promote stress-induced CSD-like responses in cortical and subcortical areas

A number of drugs, including triptans, promote migraine chronification in susceptible individuals. In rats, a period of triptan administration over 7 days can produce "latent sensitization" (14 days after discontinuation of drug) demonstrated as enhanced sensitivity to presumed migraine triggers such as environmental stress and lowered threshold for electrically induced cortical spreading depression (CSD). Here we have used fMRI to evaluate the early changes in brain networks at day 7 of sumatriptan administration that may induce latent sensitization as well as the potential response to stress. After continuous infusion of sumatriptan, rats were scanned to measure changes in resting state networks and the response to bright light environmental stress. Rats receiving sumatriptan, but not saline infusion, showed significant differences in default mode, autonomic, basal ganglia, salience, and sensorimotor networks. Bright light stress produced CSD-like responses in sumatriptan-treated but not control rats. Our data show the first brain-related changes in a rat model of medication overuse headache and suggest that this approach could be used to evaluate the multiple brain networks involved that may promote this condition.

Behavioral and neurophysiological effects of Ro 10-5824, a dopamine D4 receptor partial agonist, in common marmosets

RATIONALE

Growing evidence suggests that dopamine D4 receptors (D4Rs) are involved in controlling executive functions. We have previously demonstrated that Ro 10-5824, a D4R partial agonist, improves the performance of common marmosets in the object retrieval detour (ORD) task. However, the neural mechanisms underlying this improvement are unknown.

OBJECTIVES

We investigated the behavioral and neurophysiological effects of Ro 10-5824 in common marmosets.

METHODS

The effects of Ro 10-5824 on cognitive function were evaluated using the ORD task. The neurophysiological effects of Ro 10-5824 were investigated by quantitative electroencephalography, especially on baseline gamma band activity in the frontal cortex. The effects of Ro 10-5824 on spontaneous locomotion were also assessed.

RESULTS

Systemic administration of Ro 10-5824 at 3 mg/kg significantly increased the success rate in the ORD task. At doses of 1 and 3 mg/kg, Ro 10-5824 increased baseline gamma band activity in the frontal cortex. Ro 10-5824 had no effect on spontaneous locomotion.

CONCLUSIONS

Activation of D4R by Ro 10-5824 improves the success rate in the ORD task and increases baseline gamma band activity in the frontal cortex without affecting locomotion in common marmosets. These findings highlight the role of D4R in gamma oscillations of non-human primates. As gamma oscillations are thought to be involved in attention and behavioral inhibition, our results suggest D4R agonists may improve these cognitive functions by modulating baseline gamma band activity in the frontal cortex.

The default mode network as a biomarker for monitoring the therapeutic effects of meditation

The default mode network (DMN) is a group of anatomically separate regions in the brain found to have synchronized patterns of activation in functional magnetic resonance imaging (fMRI). Mentation associated with the DMN includes processes such as mind wandering, autobiographical memory, self-reflective thought, envisioning the future, and considering the perspective of others. Abnormalities in the DMN have been linked to symptom severity in a variety of mental disorders indicating that the DMN could be used as a biomarker for diagnosis. These correlations have also led to the use of DMN modulation as a biomarker for assessing pharmacological treatments. Concurrent research investigating the neural correlates of meditation, have associated DMN modulation with practice. Furthermore, meditative practice is increasingly understood to have a beneficial role in the treatment of mental disorders. Therefore we propose the use of DMN measures as a biomarker for monitoring the therapeutic effects of meditation practices in mental disorders. Recent findings support this perspective, and indicate the utility of DMN monitoring in understanding and developing meditative treatments for these debilitating conditions.

Neurogenetics and gene therapy for reward deficiency syndrome: are we going to the Promised Land?

INTRODUCTION

Addiction is a substantial health issue with limited treatment options approved by the FDA and as such currently available. The advent of neuroimaging techniques that link neurochemical and neurogenetic mechanisms to the reward circuitry brain function provides a framework for potential genomic-based therapies.

AREAS COVERED

Through candidate and genome-wide association studies approaches, many gene polymorphisms and clusters have been implicated in drug, food and behavioral dependence linked by the common rubric reward deficiency syndrome (RDS). The results of selective studies that include the role of epigenetics, noncoding micro RNAs in RDS behaviors especially drug abuse involving alcohol, opioids, cocaine, nicotine, pain and feeding are reviewed in this article. New targets for addiction treatment and relapse prevention, treatment alternatives such as gene therapy in animal models, and pharmacogenomics and nutrigenomics methods to manipulate transcription and gene expression are explored.

EXPERT OPINION

The recognition of the clinical benefit of early genetic testing to determine addiction risk stratification and dopaminergic agonistic, rather than antagonistic therapies are potentially the genomic-based wave of the future. In addition, further development, especially in gene transfer work and viral vector identification, could make gene therapy for RDS a possibility in the future.

Aberrant functional connectivity of default-mode network in type 2 diabetes patients

OBJECTIVES

Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables.

METHODS

Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable.

RESULTS

Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r = 0.359, p = 0.020), the time spent on Trail-Making Test-part B (r = -0.346, p = 0.025) and the insulin resistance level (r = -0.404, p = 0.024).

CONCLUSION

Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline.

KEY POINTS

• Type 2 diabetes mellitus is associated with impaired cognition • Default- mode network plays a central role in maintaining normal cognition • Network connectivity within the default mode was disrupted in type 2 diabetes patients • Decreased network connectivity was correlated with cognitive performance and insulin resistance level • Disrupted default-mode network might explain the impaired cognition in diabetic population.

Neuroimaging Biomarkers for Psychosis

BACKGROUND

Biomarkers provide clinicians with a predictable model for the diagnosis, treatment and follow-up of medical ailments. Psychiatry has lagged behind other areas of medicine in the identification of biomarkers for clinical diagnosis and treatment. In this review, we investigated the current state of neuroimaging as it pertains to biomarkers for psychosis.

METHODS

We reviewed systematic reviews and meta-analyses of the structural (sMRI), functional (fMRI), diffusion-tensor (DTI), Positron emission tomography (PET) and spectroscopy (MRS) studies of subjects at-risk or those with an established schizophrenic illness. Only articles reporting effect-sizes and confidence intervals were included in an assessment of robustness.

RESULTS

Out of the identified meta-analyses and systematic reviews, 21 studies met the inclusion criteria for assessment. There were 13 sMRI, 4 PET, 3 MRS, and 1 DTI studies. The search terms included in the current review encompassed familial high risk (FHR), clinical high risk (CHR), First episode (FES), Chronic (CSZ), schizophrenia spectrum disorders (SSD), and healthy controls (HC).

CONCLUSIONS

Currently, few neuroimaging biomarkers can be considered ready for diagnostic use in patients with psychosis. At least in part, this may be related to the challenges inherent in the current symptom-based approach to classifying these disorders. While available studies suggest a possible value of imaging biomarkers for monitoring disease progression, more systematic research is needed. To date, the best value of imaging data in psychoses has been to shed light on questions of disease pathophysiology, especially through the characterization of endophenotypes.

Imaging in drug development

Imaging has played an important part in the diagnosis of disease and development of the understanding of the underlying disease mechanisms and is now poised to make an impact in the development of new pharmaceuticals. This chapter discusses the underlying technologies that make the field ready for this challenge. In particular, the potentials of magnetic resonance imaging and functional magnetic resonance imaging are outlined, including the new methods developed to provide additional information from the scans carried out. The field of nuclear medicine has seen a rapid increase in interest as advances in radiochemistry have enabled a wide range of new radiotracers to be synthesised.

Oppositional COMT Val158Met effects on resting state functional connectivity in adolescents and adults

Prefrontal dopamine levels are relatively increased in adolescence compared to adulthood. Genetic variation of COMT (COMT Val158Met) results in lower enzymatic activity and higher dopamine availability in Met carriers. Given the dramatic changes of synaptic dopamine during adolescence, it has been suggested that effects of COMT Val158Met genotypes might have oppositional effects in adolescents and adults. The present study aims to identify such oppositional COMT Val158Met effects in adolescents and adults in prefrontal brain networks at rest. Resting state functional connectivity data were collected from cross-sectional and multicenter study sites involving 106 healthy young adults (mean age 24 ± 2.6 years), gender matched to 106 randomly chosen 14-year-olds. We selected the anterior medial prefrontal cortex (amPFC) as seed due to its important role as nexus of the executive control and default mode network. We observed a significant age-dependent reversal of COMT Val158Met effects on resting state functional connectivity between amPFC and ventrolateral as well as dorsolateral prefrontal cortex, and parahippocampal gyrus. Val homozygous adults exhibited increased and adolescents decreased connectivity compared to Met homozygotes for all reported regions. Network analyses underscored the importance of the parahippocampal gyrus as mediator of observed effects. Results of this study demonstrate that adolescent and adult resting state networks are dose-dependently and diametrically affected by COMT genotypes following a hypothetical model of dopamine function that follows an inverted U-shaped curve. This study might provide cues for the understanding of disease onset or dopaminergic treatment mechanisms in major neuropsychiatric disorders such as schizophrenia and attention deficit hyperactivity disorder.